Data-Oriented Python Programming and Debugging
Description
In “Data-Oriented Python Programming and Debugging,” you will develop Python debugging skills and learn best practices, helping you become a better data-oriented programmer. Courses in the series will explore how to write and debug code, as well as manipulate and analyze data using Python’s NumPy, pandas, and SciPy libraries. You’ll rely on the OILER framework – Orient, Investigate, Locate, Experiment, and Reflect – to systematically approach debugging and ensure your code is readable and reproducible, ensuring you produce high-quality code in all of your projects. The series concludes with a capstone project, where you’ll use these skills to debug and analyze a real-world data set, showcasing your skills in data manipulation, statistical analysis, and scientific computing.
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Subject
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Language
English
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Duration
16 weeks
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Status
Available
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U-M Credit Eligible
No
Data Science
Instructors
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Paul Resnick
Michael D. Cohen Collegiate Professor of Information
University of Michigan, School of Information
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Elle O'Brien
Lecturer IV and Research Investigator
University of Michigan, School of Information
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Anthony Whyte
Lecturer IV
University of Michigan, School of Information
Courses (4)
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Learn morePython Debugging: A Systematic Approach
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4 weeks
Learn structured debugging techniques in Python using loops, control structures, and the OILER framework to write and troubleshoot code effectively. -
Learn moreNumPy and Pandas Basics for Future Data Scientists
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4 weeks
Learn NumPy and pandas to manipulate arrays and write efficient Python code for numerical computing and data analysis. -
Learn moreStatistics with Python Using NumPy, Pandas, and SciPy
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4 weeks
Apply Python and scientific libraries like NumPy and SciPy to solve statistical problems and explore probability, distributions, and relationships in data. -
Learn morePython Debugging Capstone Project: Fixing and Extending Code
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4 weeks
Apply debugging strategies and data science tools to analyze real-world datasets and document your coding process in a capstone project.